Impact of Balloon Guide Catheters in Elderly Patients Treated with Mechanical Thrombectomy: Insights from the ROSSETTI Registry.

BACKGROUND AND PURPOSE: Several nonrandomized studies have demonstrated the effectiveness of balloon guide catheters in treating patients with anterior circulation large-vessel occlusion. However, their impact on the elderly populations has been underreported. We aimed to analyze the effect of balloon guide catheters in a cohort of elderly patients (80 years of age or older) with anterior circulation large-vessel occlusion. MATERIALS AND METHODS: Consecutive patients from June 2019 to June 2022 were collected from the ROSSETTI Registry. Demographic and clinical data, angiographic endovascular technique, and clinical outcome were compared between balloon guide catheter and non-balloon guide catheter groups. We studied the association between balloon guide catheters and the rate of complete recanalization after a single first-pass effect modified TICI 2c-3, as well as their association with functional independence at 3 months. RESULTS: A total of 808 patients were included during this period, 465 (57.5%) of whom were treated with balloon guide catheters. Patients treated with balloon guide catheters were older, had more neurologic severity at admission and lower baseline ASPECTS, and were less likely to receive IV fibrinolytics. No differences were observed in terms of the modified first-pass effect between groups (45.8 versus 39.9%, P = .096). In the multivariable regression analysis, balloon guide catheter use was not independently associated with a modified first-pass effect or the final modified TICI 2c-3, or with functional independence at 3 months. CONCLUSIONS: In our study, balloon guide catheter use during endovascular treatment of anterior circulation large-vessel occlusion in elderly patients did not predict the first-pass effect, near-complete final recanalization, or functional independence at 3 months. Further studies, including randomized clinical trials, are needed to confirm these results.

CT-Based Radiomics to Predict KRAS Mutation in CRC Patients Using a Machine Learning Algorithm: A Retrospective Study.

Colorectal cancer (CRC) is one of the most common types of cancer worldwide. The KRAS mutation is present in 30-50% of CRC patients. This mutation confers resistance to treatment with anti-EGFR therapy. This article aims at proving that computer tomography (CT)-based radiomics can predict the KRAS mutation in CRC patients. The piece is a retrospective study with 56 CRC patients from the Hospital of Santiago de Compostela, Spain. All patients had a confirmatory pathological analysis of the KRAS status. Radiomics features were obtained using an abdominal contrast enhancement CT (CECT) before applying any treatments. We used several classifiers, including AdaBoost, neural network, decision tree, support vector machine, and random forest, to predict the presence or absence of KRAS mutation. The most reliable prediction was achieved using the AdaBoost ensemble on clinical patient data, with a kappa and accuracy of 53.7% and 76.8%, respectively. The sensitivity and specificity were 73.3% and 80.8%. Using texture descriptors, the best accuracy and kappa were 73.2% and 46%, respectively, with sensitivity and specificity of 76.7% and 69.2%, also showing a correlation between texture patterns on CT images and KRAS mutation. Radiomics could help manage CRC patients, and in the future, it could have a crucial role in diagnosing CRC patients ahead of invasive methods.